Entity-Based SEO: A Beginner’s Guide (From A Novice)

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SEO (Search Engine Optimization) has long been about keywords and keyphrases.

For the last few years, however, this seems to be moving more towards Entity-based SEO (Entity SEO). I feel that Entity SEO has gained more momentum after the Helpful Content Update 2023.

I plan to keep expanding this page as a self-study resource on Entity SEO, to help me learn how to use this knowledge for better search engine rankings and user engagement.

The following are a few basics I learned about Entity SEO.

What is Entity SEO?

Entity-based SEO (Entity SEO) is optimizing webpages with semantically related entities to make them more visible and rank higher on search engines. This allows search engines to analyze the page content better and retrieve more precise information from it.

In simple words:

Entity-based SEO (Entity SEO) is a new way to help websites and webpages rank higher in search results. It focuses on understanding and connecting things (entities) that are related to a topic. This helps search engines better understand your website and show more relevant results to searchers.

Google says that an entity is anything singular, unique, well-defined, and distinguishable. An entity can be a physical object or something abstract like a color, a date, a currency, or even an idea.

“Entities are the foundation of semantic understanding by search engines and humans.”

From Keywords to Entities: A Paradigm Shift in SEO

Traditionally, SEO focused on keywords, but they have limitations, like being language-dependent and ambiguous. Entities mark a shift in how search engines interpret and process information.

For instance, the word “Apple” could refer to either the brand or the fruit “apple”, creating ambiguity (for the search engine) without context. As a result, they struggle to return accurate results.

Entities, on the other hand, provide clear contexts. They represent real-world objects, such as people, brands, products, and locations. They allow search engines to transcend language barriers and better grasp user intent, enhancing search accuracy.

Entity vs. Keyword: A Comparison

Let’s see how entity-based semantic relationships differ from keywords:

• Basic Differences: Google defines an SEO entity as something distinct, unique, well-defined, and distinguishable. Keywords, on the other hand, are typically specific or non-specific words/phrases used for search engine queries.
• Intrinsic Nature: Entities can represent both physical objects and abstract concepts, such as colors or ideas. Keywords, however, are more limited to textual representations and do not inherently convey a broader context.
• Language Boundaries: Entities transcend linguistic boundaries, maintaining consistent meanings across different languages. Keywords are inherently language-specific, meaning their interpretation can vary from one language to another.
• Search Engine Recognition: Google’s adoption of entities was driven by the need to address the issue of separate web pages from the same website ranking for multiple keyword variations, reflecting a limited understanding of content relatedness.
• Search Accuracy Enhancement: The move towards entities is part of Google’s endeavor to improve search accuracy by recognizing real-world objects and their consistent meanings, regardless of language. Keywords, while still relevant, have assumed a secondary role in this context.
• SEO Playground: While entities have become central to modern SEO strategies, contextual keywords still play a critical role in defining and supporting the understanding of these entities, bridging the gap between textual queries and conceptual understanding.

“Unlike keywords, entities are language-independent and carry universal meaning.”

Benefits of Entity SEO

• Accuracy and Relevance: Entity-based SEO ensures more accurate search results by considering user intent, context, and relationships. It eliminates ambiguity and irrelevant information.
• Language Universality: Entities transcend language limitations, allowing search engines to recognize related content across different languages.
• Enhanced Search Experience: By understanding entities, search engines deliver more meaningful results. And, users benefit from precise information related to their queries.

How Entities Work (Together) In Entity-based SEO

Entity-based SEO connects entities based on their meanings, contexts, and relationships. These semantic connections between entities allow search engines to better grasp the context of web pages and provide more relevant and accurate results to users.

For instance, consider a search query for “best laptops for students.” Without entity-based SEO, search engines might simply return a list of web pages containing the keywords “laptops” and “students”.

However, with entity-based SEO, search engines can deeply understand what the searcher is looking for.

This in-depth understanding of the search intent lets search engines show more personalized and useful results, such as comparing specific laptop models based on the needs of students, local trends, and educational discounts.

“Entity-based SEO leverages the power of semantic connections between entities to enhance SEO.”

Entity-SEO professionals enhance the semantic richness of their web by aligning websites with relevant entities on-site and off-site, establishing clear connections between them.

Entity SEO Triad: Notability, Contribution, and Prizes

Three critical factors determine an entity’s prominence (ranking factors):

1. Notability:

• Notability transcends industries.
• It compares an entity’s importance across different segments.
• An illustrative example is the difference between “Apple” as a tech company and “apple” as a fruit. Google’s algorithms can discern which entity is more notable in a given context.

2. Contributions:

• Contribution focuses on an entity’s impact within its specific industry.
• It tells the search engine how well-known are you for a particular aspect.
• For instance, an SEO expert’s history of contributions and thought leadership helps solidify their authoritative position in the field.

3. Prizes and Awards:

• Recognitions like awards, accolades, and prizes reflect an entity’s recognition and achievements.
• Notable mentions on different places on the web play a significant role in reflecting an entity’s ranking status.
• Prizes and recognitions add a layer of credibility and elevate the perceived stature of an entity within its domain.

How To Do Entity-based SEO: Brief Outline

Entity SEO is a three-step process.

• First, find the semantically related entities to your topic.
• Second, create content optimized for these entities, incorporating them strategically into your website’s title tags, meta descriptions, and body content.
• Third, build backlinks from semantically related sources. These backlinks signal search engines that your website provides authoritative and trustworthy information on the given topic.

Of course, Entity SEO has a two-way relationship with your website’s brand reputation. As your entity-based SEO efforts improve, so does the perception of your brand among users, and vice versa.

Incorporating Entities: A Practical Strategy for SEO Enhancement

Let’s expand the steps of incorporating entities into your SEO strategy:

1. Finding The Entities: Your Entity SEO Starting Point

Entity SEO begins with collecting the most relevant entities. You could use keyword research tools or simple brainstorming to identify your domain-relevant or topic-relevant entities.

More ways to identify the entities could be:

• Explore industry reports and publications: Industry-specific reports and publications can provide valuable insights into the key entities and concepts that are shaping your field.
• Analyze competitor websites: Competitive analysis can reveal the entities that are being targeted by your competitors. This information can help you refine your own entity selection and ensure that you are covering all the most important concepts in your niche.
• Utilize semantic analysis tools: Semantic analysis tools (like Google’s Natural Language API) can help you uncover hidden connections between entities within your topic area. Knowing these relationships can help you build a comprehensive and interconnected knowledge graph for your website.
• Exploring Wikipedia for Entities: Wikipedia serves as a comprehensive source of relevant entities. By searching for a specific topic, such as “Florida,” you can analyze the page for pertinent entities and integrate them into your content strategy.
• Checking Google Knowledge Graph Search API: The Google Knowledge Graph Search API, accessible even in its demo version, is a valuable tool for identifying entities within text, offering insights that can refine your SEO approach.
• Identifying Core Entities for Your Business: Start by pinpointing the central entities around which your business operates, be it a service, product, or a specific industry niche, and recognize these entities as the foundation of your SEO strategy.
• Conducting Competitor Analysis for Insights: Analyze competitor pages to understand their emphasis on entities and their linking strategies, gaining insights to adapt and apply to your content.
• Engage with your target audience: Directly interacting with your target audience through surveys, interviews, or social media discussions can provide valuable insights into the entities that are most relevant to them. This user-centric approach can help you identify entities that may not be captured by traditional research methods.

2. Using Entities in Your Content: Connecting The Dots

Once you have unearthed these entities, incorporate them seamlessly into your content.

For example, if your article is about a famous architect, entities like their notable works, architectural style, and influences can enrich your content.

This approach enhances the content’s relevance and improves search engine visibility by showcasing the interconnected nature of the entities.

3. Powering Up Structured Data: Making Content Clear to Search Engines

Structured data is a way of organizing information on a website. Search engines see structured data as a type of lens that helps more accurate reading of a website and allows presenting it more attractively.

Key points about structured data:

• Helps search engines understand content: Structured data makes it easier for search engines to understand the content of a webpage, allowing them to display the information in a more informative and visually appealing way.
• Uses specific markups: Structured data uses markups like Schema.org, Microdata, and RDFa to communicate with search engines.
• Rich snippets and other features: Structured data can make websites eligible for rich snippets, rich cards, AMPs, and knowledge graphs in search results, which can help increase click-through rates.
• Invisible to users: Structured data is added to the code of a website and is not visible to users. It helps search engines understand the context
• Not a direct ranking signal: Though structured data is not a direct ranking signal for search engines, it can indirectly help improve a website’s search engine ranking by increasing its click-through rate (CTR).

Schema markup is a type of structured data. Using schema markup makes content structure clearer, making it easier to find and more relevant in search engine result pages (SERPs)

4. Enhancing Entity SEO with Artificial Intelligence (AI)

Here are some ways to integrate Artificial Intelligence (AI) into Entity SEO, for a more nuanced, effective, and future-forward way to content optimization and user engagement:

• Accurate Entity Identification and Categorization: AI excels in precisely identifying and categorizing diverse entities, from broad concepts to specific details. This accuracy is crucial for aligning content with user search intent and preferences.
• Alignment with Search Engine Algorithms: AI’s ability to analyze and adapt to search engine algorithms ensures that content strategies are consistently optimized. It helps in understanding search patterns, user behavior, and algorithmic changes, leading to more effective SEO tactics.
• Dynamic Content Strategies Based on Entity Relationships: AI technologies are adept at analyzing and understanding the complex relationships between entities. This insight allows for dynamic content creation and curation, where content is not only relevant but also interconnected and contextually rich.
• Predictive Analysis for Trending Entities: AI tools can forecast emerging trends and popular entities within specific niches. By predicting these trends, AI empowers SEO professionals to stay ahead of the curve in content relevance.
• Enhanced User Experience through Personalization: Leveraging AI in Entity SEO can lead to highly personalized content experiences for users. AI can tailor content based on individual user preferences and search histories, making it more engaging and relevant.
• Semantic Understanding and Contextual Relevance: AI’s deep semantic understanding ensures that content is not just keyword-focused but contextually relevant. This semantic approach improves the quality and relevance of content in search results.

5. Voice Search Optimization: Making Entities Audible

Optimizing for voice search involves fine-tuning how entities are presented and understood in spoken queries, a crucial aspect of modern SEO:

• Key Role of Entities in Voice Search: Entities are central to voice search accuracy, as these searches often revolve around specific entities and seek precise information.
• Adapting Content for Voice Queries: Ensure your content is structured to answer entity-based queries directly. This involves incorporating natural language processing (NLP) techniques to mirror how people naturally ask questions in voice searches.
• Focus on Conversational Keywords: Integrate conversational keywords and phrases that are commonly used in voice searches. This includes long-tail keywords and question-based queries that align with how users verbally interact with search devices.
• Understanding User Intent in Voice Queries: Analyze and understand the user intent behind voice searches, which often differs from text-based searches. Tailor your content to address the intent, whether it’s informational, navigational, or transactional.
• Leveraging AI for Better Responses: Utilize AI tools to better predict and respond to the nuances of voice search queries. AI can help in understanding the context and subtext of spoken queries, thereby enhancing the accuracy of the responses provided.
• Semantic Richness in Content: Incorporate a semantically rich approach in your content, ensuring it aligns with the natural, conversational tone of voice searches. This includes the use of synonyms and related terms that might be used in spoken language.

6. Entity Analytics: Monitoring Entity Performance

Leverage advanced analytics tools like Google Analytics and SEMrush to understand how entities perform in searches.

These analytics help refine your SEO strategy by identifying which entities are most effective at driving traffic.

Examine and optimize the connections between these entities to enhance the interconnectedness and richness of your content.

7. Exploring Entity SEO Resources

Websites and platforms offering valuable insights on entity-based SEO:

• Koray Tugberk Gubur’s Website: A rich resource for learning about holistic SEO and entity optimization. Visit Koray Tugberk Gubur’s Website
• Moz Blog: Offers a wide range of articles and guides on all aspects of SEO, including entity SEO. Brand Entity SEO
• Search Engine Journal: A go-to platform for the latest trends and deep dives into SEO strategies. Why Entities Are Important Right Now
• Yoast SEO Blog: Provides practical advice and tutorials on SEO, including how to leverage entities effectively. Structured data awesomeness
• Google’s Webmaster Central Blog: Stay updated with Google’s own insights and updates on search algorithms and best practices. Google Webmaster Central Blog
• Schema.org Official Documentation: Understand the technical aspects of schema markup directly from the source. Schema.org Documentation
• SEMrush Blog: Offers detailed articles and case studies on various SEO techniques, including entity-based optimization. Understand Google Knowledge Panel

Best Practices: Optimizing for Entities

Optimizing for entities aligns with advanced AI trends and provides a robust, future-ready SEO strategy. Here are some best practices to effectively optimize for entities:

1. Embrace Language and Spelling Variability: Recognize that Google’s sophisticated algorithms can handle variations in spelling (like American vs. British English) and understand synonyms and semantically related terms.
2. Focus on Holistic Entity Coverage: Rather than just keyword density, concentrate on the broader context of the entire entity. Include semantically related terms and phrases (such as ‘map’, ‘travel’, ‘itinerary’) to enrich the entity’s representation.
3. Implement Schema Markup for Clarity: Use Schema.org markup to define and categorize entities within your content. This structured data approach enhances search engines’ understanding of your content, improving indexing and relevance.
4. Regular Content Refreshment: Consistently update your content to reflect evolving and emerging entities relevant to your niche. This keeps your content current and aligned with user searches and interests.
5. Building Networks of Related Entities: Develop an ecosystem of interconnected entities on your website. This network approach enriches the content and enhances the thematic strength and search visibility of your site.
6. Stay Abreast of AI and Machine Learning Advances: Keep up-to-date with the latest developments in AI and machine learning. Integrating these technologies can revolutionize your Entity SEO approach, keeping you at the forefront of digital marketing trends.

Topical Map: A Blueprint for Semantic SEO

A topical map is like a blueprint for your website’s content. It organizes information into a structured hierarchy, making it easier for both users and search engines to navigate.

Why Topical Maps Matter

• Achieving topical authority is crucial for SEO.
• Topical authority positions your site as an authority on specific topics or entities.
• Google rewards well-structured content that covers the breadth of a topic.

Structuring Your Content Network

• Create a content network for each subtopic.
• Cover related questions, explore variations, and provide comprehensive answers.
• Use logical internal links with relevant anchor texts to connect subtopics.

Creating Your Topical Map

• Start with a seed keyword that represents your main topic.
• Break down your primary topic into subcategories (subtopics).
• Each subtopic should cover all possible questions a user might have.

Tools for Topical Map SEO

Keyword Research Software:

• Drop your seed keyword into your tool.
• Filter the results to identify related subtopics.
• Use a broad keyword that represents your overall topic.

Google Sheets or Manual Creation:

• Manually create your topical map using tools like Google Sheets.
• Organize topics and subtopics hierarchically.
• Understand your website’s structure and content flow.

Screaming Frog and Sitemap Analysis:

• Use Screaming Frog to crawl your website (limit it to 200–300 pages).
• Analyze the tree graph to visualize content relationships.
• Alternatively, explore your sitemap to understand topic structures.

Bottom-of-Funnel Pages and Entities

Entity Optimization:

• Bottom-of-funnel pages often focus on a single entity.
• For example, optimizing a page for Zion National Park might involve entities like hiking and Cable Mountain.

Semantic SEO Strategy:

• Think beyond keywords—consider the entire entity.
• Entities enhance semantic relevance and improve search visibility.

Start with a Topic:

• Imagine you’re writing an article about baking fish in an oven.
• Brainstorm related entities: ingredients, cooking techniques, utensils, etc.

Map Out Entities:

• Create a topical map with your main topic at the center.
• Branch out to related entities: recipes, seafood, kitchen tools, etc.
• Think beyond keywords—focus on the entire entity.

Schema Markup for Entity SEO

Schema markup is a form of structured data that significantly enhances search engines’ grasp of web content. It helps categorize and index content more accurately, leading to potentially higher SERP visibility, and effectively enhancing Entity SEO.

Schema Implementation for Main Entities

For content centered around a single key concept, targeted schema markup is used. The appropriate schema type is selected from Schema.org based on the primary entity.

For example, a page about a person would use the Person schema to detail their name, birthdate, and achievements.

Schema Implementation for Complex Topics

In complex content involving multiple entities or processes, broader schema types are necessary. These allow for detailing a range of properties and are suitable for content that spans beyond a single entity.

For instance, a cooking-related page might use the Recipe schema, including ingredients, methods, and tools used, providing a comprehensive understanding of the topic to search engines.

Comprehensive Application Beyond Main Entities

Schema markup can describe all content facets, including secondary entities, processes, and their interrelationships. This is especially valuable in multifaceted content where different elements contribute to the overall subject.

A business website, for instance, can use schema for primary services, customer testimonials, and staff information, creating a rich, interconnected dataset.

Dynamic Schema Implementation & User Experience

Updating schema markup regularly is crucial, particularly for dynamic content areas, to ensure the data stays relevant. Schema primarily benefits search engines, but it also improves user experience.

Rich snippets, derived from schema data, offer users quick, relevant information in search results, increasing engagement and click-through rates.

Monitoring and Optimizing Schema Performance

Regular analysis and adjustment of the schema strategy are key to maintaining optimal SEO results.

Tools like Google’s Search Console can provide insights into the effectiveness of schema and highlight areas for improvement.

Knowledge Graphs: Google’s Evolution for Quality Search

Google’s enduring mission to deliver the most relevant and high-quality search results has led to significant algorithmic advancements over time.

Google’s Major Algorithm Updates

1. The Panda Update (2011): Addressing the influx of low-quality content in search results, the Panda Update focused on enhancing content quality by penalizing websites with thin, duplicate, or spammy content. This update profoundly impacted many business websites, ultimately elevating the overall standard of online content.
2. The Penguin Update (2012): Shifting its focus to combat black-hat SEO tactics, especially in link building, the Penguin Update targeted and penalized manipulative practices. At the same time, it rewarded websites employing ethical link-building strategies, promoting a more honest SEO landscape.
3. The Knowledge Graph Introduction (2012): Google revolutionized search with the introduction of the Knowledge Graph. This move aimed to transcend easily manipulated SEO tactics, offering users richer, more context-aware results. The Knowledge Graph weaves a network of entities, connecting them based on meanings, contexts, and relationships, with data sourced from platforms like the Google Knowledge Graph, LinkedIn, Wikidata, and Amazon’s product graph.
4. From Strings to Things: Marking a significant shift, Google moved from focusing on “strings” (individual keywords) to “things” (real-world entities). This change underscored the importance of understanding entities—both tangible and intangible—in providing more accurate and contextually relevant search results.

Transforming Text into Knowledge Graphs

As search engines, especially Google, evolve and become more sophisticated, they aim to organize the world’s information into a semantic web, building more meaningful and contextual Knowledge Graphs.

• Search engines construct knowledge graphs using data from various sources, like Google Knowledge Graph, LinkedIn, Wikidata, and Amazon’s product graph.
• These graphs then serve as information banks about entities and their relationships, letting search engines better understand the context of web pages.
• This deeper understanding empowers search engines to provide more relevant and accurate results to users.

Google’s approach to creating a semantic network or knowledge graph involves several steps:

1. Input Text Processing: Text inputs, ranging from web content to emails, undergo processing using Natural Language Processing (NLP) techniques.
2. Information Extraction Pipeline: This pipeline consists of multiple steps, each playing a role in building a knowledge graph from the provided text.
3. Coreference Resolution: This initial step identifies references to the same entity within the text, such as linking “Elon Musk” to subsequent mentions of “he,” thereby clarifying entity references.
4. Graph Construction: The information is structured into a graph format, where nodes represent entities (like people, places, or concepts), and their relationships are depicted through connecting lines.

Why Build A Knowledge Graph?

Every day, vast amounts of information are generated via emails, PDFs, web content, and more. Knowledge graphs serve to efficiently manage these enormous volumes of data.

They offer businesses and researchers a way to integrate unstructured text data into structured, interconnected knowledge graphs, facilitating better data management and accessibility.

Entity SEO Case Studies

SEO consultant Sara Taher (Video link: YouTube) helped Brian Cato, a local business owner, enhance his web presence using entity-based SEO.

Brian Cato aimed to enhance visibility and attract local customers by integrating geographical entities into his website. This was done by linking local landmarks and neighborhoods within his site content to relevant external resources.

This led to an immediate increase in visibility and higher search rankings. Brian’s business successfully landed on page 1 of search results, demonstrating the effectiveness of localized entity SEO.

The added context and relevance of local entities helped a more in-depth understanding of content by Google.

In another case, this is how an energy and solar panel company positioned itself higher in search rankings using entity-based SEO:

Configuring the main keyword:

• Setting up the keyword (e.g., “solar panels”) in the tool.
• Choosing the time period (e.g., 1 year) to monitor.

Incorporating entities:

• Discovering major themes related to solar panels.
• Extracting relevant terms and understanding their significance.

Semantic SEO Implementation:

• Building an information architecture and content structure.
• Working on semantics and topical authority.
• Optimizing content using semantic schema markups.

The Future of Entity SEO

The future of Entity SEO is likely to see a deeper integration of AI and machine learning.

This will lead to more dynamic content creation and curation based on entity relationships across web properties and platforms.

The result will be further personalization of user experiences and refinement of search engine results, creating a semantic web.

Key Takeaways in Entity SEO

Takeaways for anyone looking to harness the power of Entity SEO for enhanced online visibility and user engagement:

1. Prioritize Semantic Context: Entities transcend language and keywords. Focus on the meaning and relationships between entities to create content that is both contextually rich and search engine friendly.
2. Leverage Structured Data: Utilize structured data and schema markup to help search engines understand the context and relevance of your content. This approach boosts Entity SEO and enhances visibility across different search platforms.
3. Stay Updated with AI Developments: With AI and machine learning becoming increasingly integral to search algorithms, staying abreast of these technologies is crucial. They offer advanced ways to identify, categorize, and leverage entities in your SEO strategy.
4. Adapt to Voice Search Trends: Voice search is growing, and it heavily relies on entities for precise and accurate responses. Optimizing for voice search requires a deep understanding of how entities are queried and interpreted in natural language.
5. Build a Network of Related Entities: Don’t just focus on individual entities; create a web of related entities. This enriches your content and positions your website as a comprehensive resource in your domain.

FAQs

Resources

1. Emilia Gjorgjevska: Master Topical SEO: The Science, Engineering and Research Behind Topic Clusters
2. The Gray Company’s How to Level Up Internal Linking for SEO, UX, & Conversion
3. Adam Gent’s collection of case studies on internal linking
4. Cyrus Shepard’s case study of 23 Million Internal Links
5. MarketBrew.AI’s blogpost on Leveraging the Power of Link Graphs to Improve Your SEO Strategy
6. Roger Montti’s Reduced Link Graph – A Way to Rank Links

Final Words

Entities are the bedrock of semantic understanding. In the evolving SEO field, it is no longer just about keywords, but about creating meaningful connections to create a semantic web.

So, focus on optimizing for entities in your SEO strategy, from content auditing to article planning. Over time, the semantic relatedness of each entity across the web can enrich your brand presence, boosting user trust, topical authority, and search engine visibility.

So, happy optimizing!